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<div class="highlight"><pre><span></span><span class="ch">#!/usr/bin/python</span>
<span class="c1"># The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt</span>
<span class="c1">#</span>
<span class="c1">#   This example program shows how to find frontal human faces in a webcam stream using OpenCV.</span>
<span class="c1">#   It is also meant to demonstrate that rgb images from Dlib can be used with opencv by just</span>
<span class="c1">#   swapping the Red and Blue channels.</span>
<span class="c1">#</span>
<span class="c1">#   You can run this program and see the detections from your webcam by executing the</span>
<span class="c1">#   following command:</span>
<span class="c1">#       ./opencv_face_detection.py</span>
<span class="c1">#</span>
<span class="c1">#   This face detector is made using the now classic Histogram of Oriented</span>
<span class="c1">#   Gradients (HOG) feature combined with a linear classifier, an image</span>
<span class="c1">#   pyramid, and sliding window detection scheme.  This type of object detector</span>
<span class="c1">#   is fairly general and capable of detecting many types of semi-rigid objects</span>
<span class="c1">#   in addition to human faces.  Therefore, if you are interested in making</span>
<span class="c1">#   your own object detectors then read the <a href="train_object_detector.py.html">train_object_detector.py</a> example</span>
<span class="c1">#   program.  </span>
<span class="c1">#</span>
<span class="c1">#</span>
<span class="c1"># COMPILING/INSTALLING THE DLIB PYTHON INTERFACE</span>
<span class="c1">#   You can install dlib using the command:</span>
<span class="c1">#       pip install dlib</span>
<span class="c1">#</span>
<span class="c1">#   Alternatively, if you want to compile dlib yourself then go into the dlib</span>
<span class="c1">#   root folder and run:</span>
<span class="c1">#       python setup.py install</span>
<span class="c1">#</span>
<span class="c1">#   Compiling dlib should work on any operating system so long as you have</span>
<span class="c1">#   CMake installed.  On Ubuntu, this can be done easily by running the</span>
<span class="c1">#   command:</span>
<span class="c1">#       sudo apt-get install cmake</span>
<span class="c1">#</span>
<span class="c1">#   Also note that this example requires Numpy which can be installed</span>
<span class="c1">#   via the command:</span>
<span class="c1">#       pip install numpy</span>

<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">dlib</span>
<span class="kn">import</span> <span class="nn">cv2</span>

<span class="n">detector</span> <span class="o">=</span> <span class="n">dlib</span><span class="o">.</span><span class="n">get_frontal_face_detector</span><span class="p">()</span>
<span class="n">cam</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">VideoCapture</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
<span class="n">color_green</span> <span class="o">=</span> <span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">255</span><span class="p">,</span><span class="mi">0</span><span class="p">)</span>
<span class="n">line_width</span> <span class="o">=</span> <span class="mi">3</span>
<span class="k">while</span> <span class="bp">True</span><span class="p">:</span>
    <span class="n">ret_val</span><span class="p">,</span> <span class="n">img</span> <span class="o">=</span> <span class="n">cam</span><span class="o">.</span><span class="n">read</span><span class="p">()</span>
    <span class="n">rgb_image</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">cvtColor</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">cv2</span><span class="o">.</span><span class="n">COLOR_BGR2RGB</span><span class="p">)</span>
    <span class="n">dets</span> <span class="o">=</span> <span class="n">detector</span><span class="p">(</span><span class="n">rgb_image</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">det</span> <span class="ow">in</span> <span class="n">dets</span><span class="p">:</span>
        <span class="n">cv2</span><span class="o">.</span><span class="n">rectangle</span><span class="p">(</span><span class="n">img</span><span class="p">,(</span><span class="n">det</span><span class="o">.</span><span class="n">left</span><span class="p">(),</span> <span class="n">det</span><span class="o">.</span><span class="n">top</span><span class="p">()),</span> <span class="p">(</span><span class="n">det</span><span class="o">.</span><span class="n">right</span><span class="p">(),</span> <span class="n">det</span><span class="o">.</span><span class="n">bottom</span><span class="p">()),</span> <span class="n">color_green</span><span class="p">,</span> <span class="n">line_width</span><span class="p">)</span>
    <span class="n">cv2</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="s1">&#39;my webcam&#39;</span><span class="p">,</span> <span class="n">img</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">cv2</span><span class="o">.</span><span class="n">waitKey</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span> <span class="o">==</span> <span class="mi">27</span><span class="p">:</span>
        <span class="k">break</span>  <span class="c1"># esc to quit</span>
<span class="n">cv2</span><span class="o">.</span><span class="n">destroyAllWindows</span><span class="p">()</span>
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